Implementation of effective conservation planning relies on a robust understanding of the spatiotemporal distribution of the target species. In the marine realm, this is even more challenging for species rarely seen at the sea surface due to their extreme diving behavior like the sperm whales. Our study aims at (a) investigating the seasonal movements, (b) predicting the potential distribution, and (c) assessing the diel vertical behavior of this species in the Mascarene Archipelago in the south-west Indian Ocean. Using 21 satellite tracks of sperm whales and eight environmental predictors, 14 supervised machine learning algorithms were tested and compared to predict the whales' potential distribution during the wet and dry season, separately. Fourteen of the whales remained in close proximity to Mauritius, while a migratory pattern was evidenced with a synchronized departure for eight females that headed towards Rodrigues Island. The best performing algorithm was the random forest, showing a strong affinity of the whales for sea surface height during the wet season and for bottom temperature during the dry season. A more dispersed distribution was predicted during the wet season, whereas a more restricted distribution to Mauritius and Reunion waters was found during the dry season, probably related to the breeding period. A diel pattern was observed in the diving behavior, likely following the vertical migration of squids. The results of our study fill a knowledge gap regarding seasonal movements and habitat affinities of this vulnerable species, for which a regional IUCN assessment is still missing in the Indian Ocean. Our findings also confirm the great potential of machine learning algorithms in conservation planning and provide highly reproductible tools to support dynamic ocean management.Interference competition occurs when two species have similar resource requirements and one species is dominant and can suppress or exclude the subordinate species. Wolves (Canis lupus) and coyotes (C. latrans) are sympatric across much of their range in North America where white-tailed deer (Odocoileus virginianus) can be an important prey species. We assessed the extent of niche overlap between wolves and coyotes using activity, diet, and space use as evidence for interference competition during three periods related to the availability of white-tailed deer fawns in the Upper Great Lakes region of the USA. We assessed activity overlap (Δ) with data from accelerometers onboard global positioning system (GPS) collars worn by wolves (n = 11) and coyotes (n = 13). https://www.selleckchem.com/products/sb-505124.html We analyzed wolf and coyote scat to estimate dietary breadth (B) and food niche overlap (α). We used resource utilization functions (RUFs) with canid GPS location data, white-tailed deer RUFs, ruffed grouse (Bonasa umbellus) and snowshoe hare (Lepus americanus) densities, and landscape covariates to compare population-level space use. Wolves and coyotes exhibited considerable overlap in activity (Δ = 0.86-0.92), diet (B = 3.1-4.9; α = 0.76-1.0), and space use of active and inactive RUFs across time periods. Coyotes relied less on deer as prey compared to wolves and consumed greater amounts of smaller prey items. Coyotes exhibited greater population-level variation in space use compared to wolves. Additionally, while active and inactive, coyotes exhibited greater selection of some land covers as compared to wolves. Our findings lend support for interference competition between wolves and coyotes with significant overlap across resource attributes examined. The mechanisms through which wolves and coyotes coexist appear to be driven largely by how coyotes, a generalist species, exploit narrow differences in resource availability and display greater population-level plasticity in resource use.Endozoochory, a mutualistic interaction between plants and frugivores, is one of the key processes responsible for maintenance of tropical biodiversity. Islands, which have a smaller subset of plants and frugivores when compared with mainland communities, offer an interesting setting to understand the organization of plant-frugivore communities vis-a-vis the mainland sites. We examined the relative influence of functional traits and phylogenetic relationships on the plant-seed disperser interactions on an island and a mainland site. The island site allowed us to investigate the organization of the plant-seed disperser community in the natural absence of key frugivore groups (bulbuls and barbets) of Asian tropics. The endemic Narcondam Hornbill was the most abundant frugivore on the island and played a central role in the community. Species strength of frugivores (a measure of relevance of frugivores for plants) was positively associated with their abundance. Among plants, figs had the highest species strength and played a central role in the community. Island-mainland comparison revealed that the island plant-seed disperser community was more asymmetric, connected, and nested as compared to the mainland community. Neither phylogenetic relationships nor functional traits (after controlling for phylogenetic relationships) were able to explain the patterns of interactions between plants and frugivores on the island or the mainland pointing toward the diffused nature of plant-frugivore interactions. The diffused nature is a likely consequence of plasticity in foraging behavior and trait convergence that contribute to governing the interactions between plants and frugivores. This is one of the few studies to compare the plant-seed disperser communities between a tropical island and mainland and demonstrates key role played by a point-endemic frugivore in seed dispersal on island.Third-generation sequencing technologies, such as Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio), have gained popularity over the last years. These platforms can generate millions of long-read sequences. This is not only advantageous for genome sequencing projects, but also advantageous for amplicon-based high-throughput sequencing experiments, such as DNA barcoding. However, the relatively high error rates associated with these technologies still pose challenges for generating high-quality consensus sequences. Here, we present NGSpeciesID, a program which can generate highly accurate consensus sequences from long-read amplicon sequencing technologies, including ONT and PacBio. The tool includes clustering of the reads to help filter out contaminants or reads with high error rates and employs polishing strategies specific to the appropriate sequencing platform. We show that NGSpeciesID produces consensus sequences with improved usability by minimizing preprocessing and software installation and scalability by enabling rapid processing of hundreds to thousands of samples, while maintaining similar consensus accuracy as current pipelines.